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SciCrunch Registry is a curated repository of scientific resources, with a focus on biomedical resources, including tools, databases, and core facilities - visit SciCrunch to register your resource.
Data analysis service that searches PubMed literature database (abstracts) about specific relationships between proteins, genes, or keywords using a NLP-based text-mining approach. The results are returned as a graph. The synonym database used in Chilibot is available, without fee, for academic use only. Several different search methods are supported including: * searching for relationship between two genes, proteins or keywords * searching for relationships between many genes, proteins, or keywords * searching for relationships between two lists of genes, proteins, or keywords Advanced options include: * Automated hypothesis generation (graph) * Restricting context using keywords * Providing your own synonyms * Modifying synonyms provided by Chilibot * Color coding nodes with gene expression values * Special search: modulation
Proper citation: Chilibot: Gene and Protein relationships from MEDLINE (RRID:SCR_001705) Copy
Non-profit plasmid repository dedicated to helping scientists around the world share high-quality plasmids. Facilitates archiving and distributing DNA-based research reagents and associated data to scientists worldwide. Repository contains over 65,000 plasmids, including special collections on CRISPR, fluorescent proteins, and ready-to-use viral preparations. There is no cost for scientists to deposit plasmids, which saves time and money associated with shipping plasmids themselves. All plasmids are fully sequenced for validation and sequencing data is openly available. We handle the appropriate Material Transfer Agreements (MTA) with institutions, facilitating open exchange and offering intellectual property and liability protection for depositing scientists. Furthermore, we curate free educational resources for the scientific community including a blog, eBooks, video protocols, and detailed molecular biology resources.
Proper citation: Addgene (RRID:SCR_002037) Copy
Database of genetic and molecular biological information about Candida albicans. Contains information about genes and proteins, descriptions and classifications of their biological roles, molecular functions, and subcellular localizations, gene, protein, and chromosome sequence information, tools for analysis and comparison of sequences and links to literature information. Each CGD gene or open reading frame has an individual Locus Page. Genetic loci that are not tied to DNA sequence also have Locus Pages. Provides Gene Ontology, GO, to all its users. Three ontologies that comprise GO (Molecular Function, Cellular Component, and Biological Process) are used by multiple databases to annotate gene products, so that this common vocabulary can be used to compare gene products across species. Development of ontologies is ongoing in order to incorporate new information. Data submissions are welcome.
Proper citation: Candida Genome Database (RRID:SCR_002036) Copy
http://biodev.extra.cea.fr/interoporc/
Automatic prediction tool to infer protein-protein interaction networks, it is applicable for lots of species using orthology and known interactions. The interoPORC method is based on the interolog concept and combines source interaction datasets from public databases as well as clusters of orthologous proteins (PORC) available on Integr8. Users can use this page to ask InteroPorc for all species present in Integr8. Some results are already computed and users can run InteroPorc to investigate any other species. Currently, the following databases are processed and merged (with datetime of the last available public release for each database used): IntAct, MINT, DIP, and Integr8.
Proper citation: InteroPorc (RRID:SCR_002067) Copy
Statistical software tool for calling common and rare variants in analysis of pool or individual next-generation sequencing data. This software is optimized for analysis of whole-exome sequencing data and whole-genome sequencing data.
Proper citation: SNVer (RRID:SCR_002061) Copy
https://software.broadinstitute.org/gatk/
A software package to analyze next-generation resequencing data. The toolkit offers a wide variety of tools, with a primary focus on variant discovery and genotyping as well as strong emphasis on data quality assurance. Its robust architecture, powerful processing engine and high-performance computing features make it capable of taking on projects of any size. This software library makes writing efficient analysis tools using next-generation sequencing data very easy, and second it's a suite of tools for working with human medical resequencing projects such as 1000 Genomes and The Cancer Genome Atlas. These tools include things like a depth of coverage analyzers, a quality score recalibrator, a SNP/indel caller and a local realigner. (entry from Genetic Analysis Software)
Proper citation: GATK (RRID:SCR_001876) Copy
Portal providing access to all JGI genomic databases and analytical tools, sequencing projects and their status, search for and download assemblies and annotations of sequenced genomes, and interactively explore those genomes and compare them with other sequenced microbes, fungi, plants or metagenomes using specialized systems tailored to each particular class of organisms. The Department of Energy (DOE) Joint Genome Institute (JGI) is a national user facility with massive-scale DNA sequencing and analysis capabilities dedicated to advancing genomics for bioenergy and environmental applications. Beyond generating tens of trillions of DNA bases annually, the Institute develops and maintains data management systems and specialized analytical capabilities to manage and interpret complex genomic data sets, and to enable an expanding community of users around the world to analyze these data in different contexts over the web.
Proper citation: JGI Genome Portal (RRID:SCR_002383) Copy
Provides pre-calculated evolutionary conservation profiles for proteins of known structure in the PDB. Enables flexibility in setting the parameters of the calculation, and accepts optional uploads of atomic coordinates, multiple sequence alignments, and phylogenetic trees for use in the calculation of conservation profiles.
Proper citation: ConSurf Database (RRID:SCR_002320) Copy
http://www.ncbi.nlm.nih.gov/SNP/
Database as central repository for both single base nucleotide substitutions and short deletion and insertion polymorphisms. Distinguishes report of how to assay SNP from use of that SNP with individuals and populations. This separation simplifies some issues of data representation. However, these initial reports describing how to assay SNP will often be accompanied by SNP experiments measuring allele occurrence in individuals and populations. Community can contribute to this resource.
Proper citation: dbSNP (RRID:SCR_002338) Copy
http://www.yandell-lab.org/software/vaast.html
A probabilistic search tool for identifying damaged genes and their disease-causing variants in personal genome sequences. VAAST combines elements of phylogenetic conservation, amino acid substitution, and aggregative approaches to variant prioritization into a single unified likelihood-framework that allows users to accurately identify damaged genes and deleterious variants. The software can score both coding (SNV, indel and splice site) and non-coding variants (SNV), evaluating the cumulative impact of both types of variants simultaneously. It can identify rare variants causing rare genetic diseases and can also use both rare and common variants to identify genes responsible for common diseases.
Proper citation: VAAST (RRID:SCR_002179) Copy
An open-source, web-based platform and suite of software tools for for sharing heterogeneous scientific research datasets, models or simulations, processes and research outcomes - and collaborations between scientists. It preserves associations between them, along with information about the people and organizations involved. Underpinning SEEK is the ISA infrastructure, a standard format for describing how individual experiments are aggregated into wider studies and investigations. Within SEEK, ISA has been extended and is configurable to allow the structure to be used outside of Biology. SEEK is incorporating semantic technology allowing sophisticated queries over the data, yet without getting in the way of your users. Access to the RESTful API to access the data within SEEK is available.
Proper citation: SEEK (RRID:SCR_002651) Copy
https://simtk.org/home/simvascular
Open source software suite for cardiovascular simulation. It includes code for reading 3D images, segmenting structures, generating models and meshes, and modeling blood flow in deformable vessels. The suite also includes tools for physiologic boundary conditions, fluid structure interaction, and an accurate and efficient finite element Navier-Stokes solver. Commercial components have been used in the simulation process, and for these components, the project attempts to provide interfaces that allow substitution of open source components. The SimVascular project is derived from the ASPIRE2 software project and includes modified portions of PHASTA from RPI/SCOREC.
Proper citation: SimVascular (RRID:SCR_002686) Copy
The free Segway software package contains a novel method for analyzing multiple tracks of functional genomics data. The method uses a dynamic Bayesian network (DBN) model, which enables it to analyze the entire genome at 1-bp resolution even in the face of heterogeneous patterns of missing data. This method is the first application of DBN techniques to genome-scale data and the first genomic segmentation method designed for use with the maximum resolution data available from ChIP-seq experiments without downsampling. Segway uses the Graphical Models Toolkit (GMTK) for efficient DBN inference. The software has extensive documentation and was designed from the outset with external users in mind.
Proper citation: Segway - a way to segment the genome (RRID:SCR_004206) Copy
A collection of bioinformatics tools that can be pieced together in a very easy and flexible manner to perform both simple and complex tasks. The Biopieces work on a data stream in such a way that the data stream can be passed through several different Biopieces, each performing one specific task: modifying or adding records to the data stream, creating plots, or uploading data to databases and web services. The Biopieces are executed in a command line environment where the data stream is initialized by specific Biopieces which read data from files, databases, or web services, and output records to the data stream that is passed to downstream Biopieces until the data stream is terminated at the end of the analysis. The advantage of the Biopieces is that a user can easily solve simple and complex tasks without having any programming experience. Moreover, since the data format used to pass data between Biopieces is text based, different developers can quickly create new Biopieces in their favorite programming language - and all the Biopieces will maintain compatibility. Finally, templates exist for creating new Biopieces in Perl and Ruby. There are currently ~190 Biopieces (March 2014).
Proper citation: Biopieces (RRID:SCR_005783) Copy
http://www.biochem.ucl.ac.uk/bsm/virus_database/VIDA3/VIDA.html
VIDA contains a collection of homologous protein families derived from open reading frames from complete and partial virus genomes. For each family, users can get an alignment of the conserved regions, functional and taxonomy information, and links to DNA sequences and structures. * Search homologous protein families from particular virus families * Links to complete genome sequence: Arteriviridae, Coronaviridae, Herpesviridae, Poxviridae The Virus Database at University College London has been developed as a system to organize animal virus open reading frame sequences. All known and predicted protein sequences from complete and partial genomes of particular virus families are extracted from GenBank and filtered to remove 100% redundancy. On the basis of sequence similarity the sequences are then clustered into homologous protein families (HPFs). The families are enriched with annotations including function and functional classification, related protein structures, taxonomy, length of the proteins, boundaries of the conserved region/s, virus-specific gene name and links to EMBL entries and SWISSPROT., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.
Proper citation: VIDA (RRID:SCR_007111) Copy
http://cudasw.sourceforge.net/
CUDASW++ is a bioinformatics software for Smith-Waterman protein database searches that takes advantage of the massively parallel CUDA architecture of NVIDIA Tesla GPUs to perform sequence searches 10x-50x faster than NCBI BLAST. In this algorithm, we deeply explore the SIMT (Single Instruction, Multiple Thread) and virtualized SIMD (Single Instruction, Multiple Data) abstractions to achieve fast speed. This algorithm has been fully tested on Tesla C1060, Tesla C2050, GeForce GTX 280 and GTX 295 graphics cards, and has been incorporated to NVIDIA Tesla Bio Workbench. * Operating System: Linux * Programming language: CUDA and C * Other requirements: CUDA SDK and Toolkits 2.0 or higher
Proper citation: CUDASW++ (RRID:SCR_008862) Copy
http://bioen-compbio.bioen.illinois.edu/FusionHunter/
Software for identifying fusion transcripts using paired-end RNA-seq.
Proper citation: FusionHunter (RRID:SCR_011895) Copy
https://github.com/gaow/genetic-analysis-software/blob/master/pages/GLUE.md
THIS RESOURCE IS NO LONGER IN SERVCE, documented September 6, 2016. A web interface to several commonly used statistical genetics programs, including Linkage, Genehunter, Merlin, Unphased, and Transmit. It simplifies their use through graphical selection of program options, automation of multiple analyses, and viewing of graphical output. GLUE is available to HGMP account holders; registration is free to all academic users., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.
Proper citation: GLUE (RRID:SCR_009211) Copy
http://www.well.ox.ac.uk/~mfarrall/twoloc.htm
Software package for analyzing two-locus susceptibility gene models in affected sib-pair data (entry from Genetic Analysis Software)
Proper citation: TWOLOC (RRID:SCR_009230) Copy
http://www.daimi.au.dk/~mailund/GeneRecon/
Software application for linkage disequilibrium mapping using coalescent theory. It is based on a Bayesian Markov-chain Monte Carlo (MCMC) method for fine-scale linkage-disequilibrium gene mapping using high-density marker maps. GeneRecon explicitly models the genealogy of a sample of the case chromosomes in the vicinity of a disease locus. Given case and control data in the form of genotype or haplotype information, it estimates a number of parameters, most importantly, the disease position. (entry from Genetic Analysis Software)
Proper citation: GENERECON (RRID:SCR_009195) Copy
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